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<div class="title">shot_local_estimator_omp.h</div>  </div>
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<div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno">    1</span>&#160;<span class="comment">/*</span></div>
<div class="line"><a name="l00002"></a><span class="lineno">    2</span>&#160;<span class="comment"> * shot_local_estimator.h</span></div>
<div class="line"><a name="l00003"></a><span class="lineno">    3</span>&#160;<span class="comment"> *</span></div>
<div class="line"><a name="l00004"></a><span class="lineno">    4</span>&#160;<span class="comment"> *  Created on: Mar 24, 2012</span></div>
<div class="line"><a name="l00005"></a><span class="lineno">    5</span>&#160;<span class="comment"> *      Author: aitor</span></div>
<div class="line"><a name="l00006"></a><span class="lineno">    6</span>&#160;<span class="comment"> */</span></div>
<div class="line"><a name="l00007"></a><span class="lineno">    7</span>&#160; </div>
<div class="line"><a name="l00008"></a><span class="lineno">    8</span>&#160;<span class="preprocessor">#ifndef REC_FRAMEWORK_SHOT_LOCAL_ESTIMATOR_OMP_H_</span></div>
<div class="line"><a name="l00009"></a><span class="lineno">    9</span>&#160;<span class="preprocessor">#define REC_FRAMEWORK_SHOT_LOCAL_ESTIMATOR_OMP_H_</span></div>
<div class="line"><a name="l00010"></a><span class="lineno">   10</span>&#160; </div>
<div class="line"><a name="l00011"></a><span class="lineno">   11</span>&#160;<span class="preprocessor">#include &lt;pcl/apps/3d_rec_framework/feature_wrapper/local/local_estimator.h&gt;</span></div>
<div class="line"><a name="l00012"></a><span class="lineno">   12</span>&#160;<span class="preprocessor">#include &lt;pcl/apps/3d_rec_framework/feature_wrapper/normal_estimator.h&gt;</span></div>
<div class="line"><a name="l00013"></a><span class="lineno">   13</span>&#160;<span class="preprocessor">#include &lt;pcl/features/shot_omp.h&gt;</span></div>
<div class="line"><a name="l00014"></a><span class="lineno">   14</span>&#160;<span class="preprocessor">#include &lt;pcl/io/pcd_io.h&gt;</span></div>
<div class="line"><a name="l00015"></a><span class="lineno">   15</span>&#160; </div>
<div class="line"><a name="l00016"></a><span class="lineno">   16</span>&#160;<span class="keyword">namespace </span>pcl</div>
<div class="line"><a name="l00017"></a><span class="lineno">   17</span>&#160;{</div>
<div class="line"><a name="l00018"></a><span class="lineno">   18</span>&#160;  <span class="keyword">namespace </span>rec_3d_framework</div>
<div class="line"><a name="l00019"></a><span class="lineno">   19</span>&#160;  {</div>
<div class="line"><a name="l00020"></a><span class="lineno">   20</span>&#160;    <span class="keyword">template</span>&lt;<span class="keyword">typename</span> Po<span class="keywordtype">int</span>InT, <span class="keyword">typename</span> FeatureT&gt;</div>
<div class="line"><a name="l00021"></a><span class="lineno"><a class="line" href="classpcl_1_1rec__3d__framework_1_1_s_h_o_t_local_estimation_o_m_p.html">   21</a></span>&#160;      <span class="keyword">class </span><a class="code" href="classpcl_1_1rec__3d__framework_1_1_s_h_o_t_local_estimation_o_m_p.html">SHOTLocalEstimationOMP</a> : <span class="keyword">public</span> <a class="code" href="classpcl_1_1rec__3d__framework_1_1_local_estimator.html">LocalEstimator</a>&lt;PointInT, FeatureT&gt;</div>
<div class="line"><a name="l00022"></a><span class="lineno">   22</span>&#160;      {</div>
<div class="line"><a name="l00023"></a><span class="lineno">   23</span>&#160; </div>
<div class="line"><a name="l00024"></a><span class="lineno">   24</span>&#160;        <span class="keyword">typedef</span> <span class="keyword">typename</span> pcl::PointCloud&lt;PointInT&gt;::Ptr PointInTPtr;</div>
<div class="line"><a name="l00025"></a><span class="lineno">   25</span>&#160;        <span class="keyword">typedef</span> <span class="keyword">typename</span> pcl::PointCloud&lt;FeatureT&gt;::Ptr FeatureTPtr;</div>
<div class="line"><a name="l00026"></a><span class="lineno">   26</span>&#160;        <span class="keyword">typedef</span> <a class="code" href="classpcl_1_1_point_cloud.html">pcl::PointCloud&lt;pcl::PointXYZ&gt;</a> <a class="code" href="classpcl_1_1_point_cloud.html">KeypointCloud</a>;</div>
<div class="line"><a name="l00027"></a><span class="lineno">   27</span>&#160; </div>
<div class="line"><a name="l00028"></a><span class="lineno">   28</span>&#160;        <span class="keyword">using</span> <a class="code" href="classpcl_1_1rec__3d__framework_1_1_local_estimator.html">LocalEstimator&lt;PointInT, FeatureT&gt;::support_radius_</a>;</div>
<div class="line"><a name="l00029"></a><span class="lineno">   29</span>&#160;        <span class="keyword">using</span> <a class="code" href="classpcl_1_1rec__3d__framework_1_1_local_estimator.html">LocalEstimator&lt;PointInT, FeatureT&gt;::normal_estimator_</a>;</div>
<div class="line"><a name="l00030"></a><span class="lineno">   30</span>&#160;        <span class="keyword">using</span> <a class="code" href="classpcl_1_1rec__3d__framework_1_1_local_estimator.html">LocalEstimator&lt;PointInT, FeatureT&gt;::keypoint_extractor_</a>;</div>
<div class="line"><a name="l00031"></a><span class="lineno">   31</span>&#160;        <span class="keyword">using</span> <a class="code" href="classpcl_1_1rec__3d__framework_1_1_local_estimator.html">LocalEstimator&lt;PointInT, FeatureT&gt;::neighborhood_indices_</a>;</div>
<div class="line"><a name="l00032"></a><span class="lineno">   32</span>&#160;        <span class="keyword">using</span> <a class="code" href="classpcl_1_1rec__3d__framework_1_1_local_estimator.html">LocalEstimator&lt;PointInT, FeatureT&gt;::neighborhood_dist_</a>;</div>
<div class="line"><a name="l00033"></a><span class="lineno">   33</span>&#160;        <span class="keyword">using</span> <a class="code" href="classpcl_1_1rec__3d__framework_1_1_local_estimator.html">LocalEstimator&lt;PointInT, FeatureT&gt;::adaptative_MLS_</a>;</div>
<div class="line"><a name="l00034"></a><span class="lineno">   34</span>&#160; </div>
<div class="line"><a name="l00035"></a><span class="lineno">   35</span>&#160;      <span class="keyword">public</span>:</div>
<div class="line"><a name="l00036"></a><span class="lineno">   36</span>&#160;        <span class="keywordtype">bool</span></div>
<div class="line"><a name="l00037"></a><span class="lineno">   37</span>&#160;        estimate (PointInTPtr &amp; in, PointInTPtr &amp; processed, PointInTPtr &amp; keypoints, FeatureTPtr &amp; signatures)</div>
<div class="line"><a name="l00038"></a><span class="lineno">   38</span>&#160;        {</div>
<div class="line"><a name="l00039"></a><span class="lineno">   39</span>&#160;          <span class="keywordflow">if</span> (!normal_estimator_)</div>
<div class="line"><a name="l00040"></a><span class="lineno">   40</span>&#160;          {</div>
<div class="line"><a name="l00041"></a><span class="lineno">   41</span>&#160;            PCL_ERROR(<span class="stringliteral">&quot;SHOTLocalEstimationOMP :: This feature needs normals... please provide a normal estimator\n&quot;</span>);</div>
<div class="line"><a name="l00042"></a><span class="lineno">   42</span>&#160;            <span class="keywordflow">return</span> <span class="keyword">false</span>;</div>
<div class="line"><a name="l00043"></a><span class="lineno">   43</span>&#160;          }</div>
<div class="line"><a name="l00044"></a><span class="lineno">   44</span>&#160; </div>
<div class="line"><a name="l00045"></a><span class="lineno">   45</span>&#160;          <span class="keywordflow">if</span> (keypoint_extractor_.size() == 0)</div>
<div class="line"><a name="l00046"></a><span class="lineno">   46</span>&#160;          {</div>
<div class="line"><a name="l00047"></a><span class="lineno">   47</span>&#160;            PCL_ERROR(<span class="stringliteral">&quot;SHOTLocalEstimationOMP :: This feature needs a keypoint extractor... please provide one\n&quot;</span>);</div>
<div class="line"><a name="l00048"></a><span class="lineno">   48</span>&#160;            <span class="keywordflow">return</span> <span class="keyword">false</span>;</div>
<div class="line"><a name="l00049"></a><span class="lineno">   49</span>&#160;          }</div>
<div class="line"><a name="l00050"></a><span class="lineno">   50</span>&#160; </div>
<div class="line"><a name="l00051"></a><span class="lineno">   51</span>&#160;          pcl::PointCloud&lt;pcl::Normal&gt;::Ptr normals (<span class="keyword">new</span> <a class="code" href="classpcl_1_1_point_cloud.html">pcl::PointCloud&lt;pcl::Normal&gt;</a>);</div>
<div class="line"><a name="l00052"></a><span class="lineno">   52</span>&#160;          <a class="code" href="classpcl_1_1_moving_least_squares.html">pcl::MovingLeastSquares&lt;PointInT, PointInT&gt;</a> mls;</div>
<div class="line"><a name="l00053"></a><span class="lineno">   53</span>&#160;          <span class="keywordflow">if</span> (adaptative_MLS_)</div>
<div class="line"><a name="l00054"></a><span class="lineno">   54</span>&#160;          {</div>
<div class="line"><a name="l00055"></a><span class="lineno">   55</span>&#160;            <span class="keyword">typename</span> search::KdTree&lt;PointInT&gt;::Ptr tree;</div>
<div class="line"><a name="l00056"></a><span class="lineno">   56</span>&#160;            Eigen::Vector4f centroid_cluster;</div>
<div class="line"><a name="l00057"></a><span class="lineno">   57</span>&#160;            <a class="code" href="group__common.html#gaf5729fae15603888b49743b118025290">pcl::compute3DCentroid</a> (*in, centroid_cluster);</div>
<div class="line"><a name="l00058"></a><span class="lineno">   58</span>&#160;            <span class="keywordtype">float</span> dist_to_sensor = centroid_cluster.norm ();</div>
<div class="line"><a name="l00059"></a><span class="lineno">   59</span>&#160;            <span class="keywordtype">float</span> sigma = dist_to_sensor * 0.01f;</div>
<div class="line"><a name="l00060"></a><span class="lineno">   60</span>&#160;            mls.<a class="code" href="classpcl_1_1_moving_least_squares.html#ab0865f62d90c9fb0f45dd96e587fe84e">setSearchMethod</a> (tree);</div>
<div class="line"><a name="l00061"></a><span class="lineno">   61</span>&#160;            mls.<a class="code" href="classpcl_1_1_moving_least_squares.html#ae5e4d16c7aae631ef02bf1ee843bd55e">setSearchRadius</a> (sigma);</div>
<div class="line"><a name="l00062"></a><span class="lineno">   62</span>&#160;            mls.<a class="code" href="classpcl_1_1_moving_least_squares.html#ac29ad97b98353d64ce64e2ff924f7d20">setUpsamplingMethod</a> (mls.SAMPLE_LOCAL_PLANE);</div>
<div class="line"><a name="l00063"></a><span class="lineno">   63</span>&#160;            mls.<a class="code" href="classpcl_1_1_moving_least_squares.html#a8efa7671c4b24700c2f22f63affdce9b">setUpsamplingRadius</a> (0.002);</div>
<div class="line"><a name="l00064"></a><span class="lineno">   64</span>&#160;            mls.<a class="code" href="classpcl_1_1_moving_least_squares.html#ac2c814527e15d4d3ff9a5ba5864b842d">setUpsamplingStepSize</a> (0.001);</div>
<div class="line"><a name="l00065"></a><span class="lineno">   65</span>&#160;          }</div>
<div class="line"><a name="l00066"></a><span class="lineno">   66</span>&#160; </div>
<div class="line"><a name="l00067"></a><span class="lineno">   67</span>&#160;          normals.reset (<span class="keyword">new</span> <a class="code" href="classpcl_1_1_point_cloud.html">pcl::PointCloud&lt;pcl::Normal&gt;</a>);</div>
<div class="line"><a name="l00068"></a><span class="lineno">   68</span>&#160;          {</div>
<div class="line"><a name="l00069"></a><span class="lineno">   69</span>&#160;            <a class="code" href="classpcl_1_1_scope_time.html">pcl::ScopeTime</a> t (<span class="stringliteral">&quot;Compute normals&quot;</span>);</div>
<div class="line"><a name="l00070"></a><span class="lineno">   70</span>&#160;            normal_estimator_-&gt;estimate (in, processed, normals);</div>
<div class="line"><a name="l00071"></a><span class="lineno">   71</span>&#160;          }</div>
<div class="line"><a name="l00072"></a><span class="lineno">   72</span>&#160; </div>
<div class="line"><a name="l00073"></a><span class="lineno">   73</span>&#160;          <span class="keywordflow">if</span> (adaptative_MLS_)</div>
<div class="line"><a name="l00074"></a><span class="lineno">   74</span>&#160;          {</div>
<div class="line"><a name="l00075"></a><span class="lineno">   75</span>&#160;            mls.<a class="code" href="classpcl_1_1_p_c_l_base.html#a1952d7101f3942bac3b69ed55c1ca7ea">setInputCloud</a> (processed);</div>
<div class="line"><a name="l00076"></a><span class="lineno">   76</span>&#160; </div>
<div class="line"><a name="l00077"></a><span class="lineno">   77</span>&#160;            PointInTPtr filtered (<span class="keyword">new</span> <a class="code" href="classpcl_1_1_point_cloud.html">pcl::PointCloud&lt;PointInT&gt;</a>);</div>
<div class="line"><a name="l00078"></a><span class="lineno">   78</span>&#160;            mls.<a class="code" href="classpcl_1_1_moving_least_squares.html#ad168be16626ea58d1c31c321bd1d980f">process</a> (*filtered);</div>
<div class="line"><a name="l00079"></a><span class="lineno">   79</span>&#160; </div>
<div class="line"><a name="l00080"></a><span class="lineno">   80</span>&#160;            processed.reset (<span class="keyword">new</span> <a class="code" href="classpcl_1_1_point_cloud.html">pcl::PointCloud&lt;PointInT&gt;</a>);</div>
<div class="line"><a name="l00081"></a><span class="lineno">   81</span>&#160;            normals.reset (<span class="keyword">new</span> <a class="code" href="classpcl_1_1_point_cloud.html">pcl::PointCloud&lt;pcl::Normal&gt;</a>);</div>
<div class="line"><a name="l00082"></a><span class="lineno">   82</span>&#160;            {</div>
<div class="line"><a name="l00083"></a><span class="lineno">   83</span>&#160;              <a class="code" href="classpcl_1_1_scope_time.html">pcl::ScopeTime</a> t (<span class="stringliteral">&quot;Compute normals after MLS&quot;</span>);</div>
<div class="line"><a name="l00084"></a><span class="lineno">   84</span>&#160;              filtered-&gt;is_dense = <span class="keyword">false</span>;</div>
<div class="line"><a name="l00085"></a><span class="lineno">   85</span>&#160;              normal_estimator_-&gt;estimate (filtered, processed, normals);</div>
<div class="line"><a name="l00086"></a><span class="lineno">   86</span>&#160;            }</div>
<div class="line"><a name="l00087"></a><span class="lineno">   87</span>&#160;          }</div>
<div class="line"><a name="l00088"></a><span class="lineno">   88</span>&#160; </div>
<div class="line"><a name="l00089"></a><span class="lineno">   89</span>&#160;          this-&gt;computeKeypoints(processed, keypoints, normals);</div>
<div class="line"><a name="l00090"></a><span class="lineno">   90</span>&#160;          std::cout &lt;&lt; <span class="stringliteral">&quot; &quot;</span> &lt;&lt; normals-&gt;<a class="code" href="classpcl_1_1_point_cloud.html#af16a62638198313b9c093127c492c884">points</a>.size() &lt;&lt; <span class="stringliteral">&quot; &quot;</span> &lt;&lt; processed-&gt;points.size() &lt;&lt; std::endl;</div>
<div class="line"><a name="l00091"></a><span class="lineno">   91</span>&#160; </div>
<div class="line"><a name="l00092"></a><span class="lineno">   92</span>&#160;          <span class="keywordflow">if</span> (keypoints-&gt;points.size () == 0)</div>
<div class="line"><a name="l00093"></a><span class="lineno">   93</span>&#160;          {</div>
<div class="line"><a name="l00094"></a><span class="lineno">   94</span>&#160;            PCL_WARN(<span class="stringliteral">&quot;SHOTLocalEstimationOMP :: No keypoints were found\n&quot;</span>);</div>
<div class="line"><a name="l00095"></a><span class="lineno">   95</span>&#160;            <span class="keywordflow">return</span> <span class="keyword">false</span>;</div>
<div class="line"><a name="l00096"></a><span class="lineno">   96</span>&#160;          }</div>
<div class="line"><a name="l00097"></a><span class="lineno">   97</span>&#160; </div>
<div class="line"><a name="l00098"></a><span class="lineno">   98</span>&#160;          <span class="comment">//compute signatures</span></div>
<div class="line"><a name="l00099"></a><span class="lineno">   99</span>&#160;          <span class="keyword">typedef</span> <span class="keyword">typename</span> <a class="code" href="classpcl_1_1_s_h_o_t_estimation_o_m_p.html">pcl::SHOTEstimationOMP&lt;PointInT, pcl::Normal, pcl::SHOT352&gt;</a> SHOTEstimator;</div>
<div class="line"><a name="l00100"></a><span class="lineno">  100</span>&#160;          <span class="keyword">typename</span> pcl::search::KdTree&lt;PointInT&gt;::Ptr tree (<span class="keyword">new</span> <a class="code" href="classpcl_1_1search_1_1_kd_tree.html">pcl::search::KdTree&lt;PointInT&gt;</a>);</div>
<div class="line"><a name="l00101"></a><span class="lineno">  101</span>&#160;          tree-&gt;<a class="code" href="classpcl_1_1search_1_1_kd_tree.html#a457ebf1fc8f25e3b45d0bf9d55880f6f">setInputCloud</a> (processed);</div>
<div class="line"><a name="l00102"></a><span class="lineno">  102</span>&#160; </div>
<div class="line"><a name="l00103"></a><span class="lineno">  103</span>&#160;          pcl::PointCloud&lt;pcl::SHOT352&gt;::Ptr shots (<span class="keyword">new</span> <a class="code" href="classpcl_1_1_point_cloud.html">pcl::PointCloud&lt;pcl::SHOT352&gt;</a>);</div>
<div class="line"><a name="l00104"></a><span class="lineno">  104</span>&#160;          SHOTEstimator shot_estimate;</div>
<div class="line"><a name="l00105"></a><span class="lineno">  105</span>&#160;          shot_estimate.setNumberOfThreads (8);</div>
<div class="line"><a name="l00106"></a><span class="lineno">  106</span>&#160;          shot_estimate.setSearchMethod (tree);</div>
<div class="line"><a name="l00107"></a><span class="lineno">  107</span>&#160;          shot_estimate.setInputCloud (keypoints);</div>
<div class="line"><a name="l00108"></a><span class="lineno">  108</span>&#160;          shot_estimate.setSearchSurface(processed);</div>
<div class="line"><a name="l00109"></a><span class="lineno">  109</span>&#160;          shot_estimate.setInputNormals (normals);</div>
<div class="line"><a name="l00110"></a><span class="lineno">  110</span>&#160;          shot_estimate.setRadiusSearch (support_radius_);</div>
<div class="line"><a name="l00111"></a><span class="lineno">  111</span>&#160; </div>
<div class="line"><a name="l00112"></a><span class="lineno">  112</span>&#160;          {</div>
<div class="line"><a name="l00113"></a><span class="lineno">  113</span>&#160;            <a class="code" href="classpcl_1_1_scope_time.html">pcl::ScopeTime</a> t (<span class="stringliteral">&quot;Compute SHOT&quot;</span>);</div>
<div class="line"><a name="l00114"></a><span class="lineno">  114</span>&#160;            shot_estimate.compute (*shots);</div>
<div class="line"><a name="l00115"></a><span class="lineno">  115</span>&#160;          }</div>
<div class="line"><a name="l00116"></a><span class="lineno">  116</span>&#160; </div>
<div class="line"><a name="l00117"></a><span class="lineno">  117</span>&#160;          signatures-&gt;resize (shots-&gt;<a class="code" href="classpcl_1_1_point_cloud.html#af16a62638198313b9c093127c492c884">points</a>.size ());</div>
<div class="line"><a name="l00118"></a><span class="lineno">  118</span>&#160;          signatures-&gt;width = <span class="keyword">static_cast&lt;</span><span class="keywordtype">int</span><span class="keyword">&gt;</span> (shots-&gt;<a class="code" href="classpcl_1_1_point_cloud.html#af16a62638198313b9c093127c492c884">points</a>.size ());</div>
<div class="line"><a name="l00119"></a><span class="lineno">  119</span>&#160;          signatures-&gt;height = 1;</div>
<div class="line"><a name="l00120"></a><span class="lineno">  120</span>&#160; </div>
<div class="line"><a name="l00121"></a><span class="lineno">  121</span>&#160;          <span class="keywordtype">int</span> size_feat = <span class="keyword">sizeof</span>(signatures-&gt;points[0].histogram) / <span class="keyword">sizeof</span>(<span class="keywordtype">float</span>);</div>
<div class="line"><a name="l00122"></a><span class="lineno">  122</span>&#160; </div>
<div class="line"><a name="l00123"></a><span class="lineno">  123</span>&#160;          <span class="keywordtype">int</span> good = 0;</div>
<div class="line"><a name="l00124"></a><span class="lineno">  124</span>&#160;          <span class="keywordflow">for</span> (<span class="keywordtype">size_t</span> k = 0; k &lt; shots-&gt;<a class="code" href="classpcl_1_1_point_cloud.html#af16a62638198313b9c093127c492c884">points</a>.size (); k++)</div>
<div class="line"><a name="l00125"></a><span class="lineno">  125</span>&#160;          {</div>
<div class="line"><a name="l00126"></a><span class="lineno">  126</span>&#160; </div>
<div class="line"><a name="l00127"></a><span class="lineno">  127</span>&#160;            <span class="keywordtype">int</span> NaNs = 0;</div>
<div class="line"><a name="l00128"></a><span class="lineno">  128</span>&#160;            <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i &lt; size_feat; i++)</div>
<div class="line"><a name="l00129"></a><span class="lineno">  129</span>&#160;            {</div>
<div class="line"><a name="l00130"></a><span class="lineno">  130</span>&#160;              <span class="keywordflow">if</span> (!pcl_isfinite(shots-&gt;<a class="code" href="classpcl_1_1_point_cloud.html#af16a62638198313b9c093127c492c884">points</a>[k].descriptor[i]))</div>
<div class="line"><a name="l00131"></a><span class="lineno">  131</span>&#160;                NaNs++;</div>
<div class="line"><a name="l00132"></a><span class="lineno">  132</span>&#160;            }</div>
<div class="line"><a name="l00133"></a><span class="lineno">  133</span>&#160; </div>
<div class="line"><a name="l00134"></a><span class="lineno">  134</span>&#160;            <span class="keywordflow">if</span> (NaNs == 0)</div>
<div class="line"><a name="l00135"></a><span class="lineno">  135</span>&#160;            {</div>
<div class="line"><a name="l00136"></a><span class="lineno">  136</span>&#160;              <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i &lt; size_feat; i++)</div>
<div class="line"><a name="l00137"></a><span class="lineno">  137</span>&#160;              {</div>
<div class="line"><a name="l00138"></a><span class="lineno">  138</span>&#160;                signatures-&gt;points[good].histogram[i] = shots-&gt;<a class="code" href="classpcl_1_1_point_cloud.html#af16a62638198313b9c093127c492c884">points</a>[k].descriptor[i];</div>
<div class="line"><a name="l00139"></a><span class="lineno">  139</span>&#160;              }</div>
<div class="line"><a name="l00140"></a><span class="lineno">  140</span>&#160; </div>
<div class="line"><a name="l00141"></a><span class="lineno">  141</span>&#160;              good++;</div>
<div class="line"><a name="l00142"></a><span class="lineno">  142</span>&#160;            }</div>
<div class="line"><a name="l00143"></a><span class="lineno">  143</span>&#160;          }</div>
<div class="line"><a name="l00144"></a><span class="lineno">  144</span>&#160; </div>
<div class="line"><a name="l00145"></a><span class="lineno">  145</span>&#160;          signatures-&gt;resize (good);</div>
<div class="line"><a name="l00146"></a><span class="lineno">  146</span>&#160;          signatures-&gt;width = good;</div>
<div class="line"><a name="l00147"></a><span class="lineno">  147</span>&#160; </div>
<div class="line"><a name="l00148"></a><span class="lineno">  148</span>&#160;          <span class="keywordflow">return</span> <span class="keyword">true</span>;</div>
<div class="line"><a name="l00149"></a><span class="lineno">  149</span>&#160; </div>
<div class="line"><a name="l00150"></a><span class="lineno">  150</span>&#160;        }</div>
<div class="line"><a name="l00151"></a><span class="lineno">  151</span>&#160; </div>
<div class="line"><a name="l00152"></a><span class="lineno">  152</span>&#160;      };</div>
<div class="line"><a name="l00153"></a><span class="lineno">  153</span>&#160;  }</div>
<div class="line"><a name="l00154"></a><span class="lineno">  154</span>&#160;}</div>
<div class="line"><a name="l00155"></a><span class="lineno">  155</span>&#160; </div>
<div class="line"><a name="l00156"></a><span class="lineno">  156</span>&#160;<span class="preprocessor">#endif </span><span class="comment">/* REC_FRAMEWORK_SHOT_LOCAL_ESTIMATOR_OMP_H_ */</span><span class="preprocessor"></span></div>
<div class="ttc" id="aclasspcl_1_1_moving_least_squares_html"><div class="ttname"><a href="classpcl_1_1_moving_least_squares.html">pcl::MovingLeastSquares</a></div><div class="ttdoc">MovingLeastSquares represent an implementation of the MLS (Moving Least Squares) algorithm for data s...</div><div class="ttdef"><b>Definition:</b> mls.h:66</div></div>
<div class="ttc" id="aclasspcl_1_1_moving_least_squares_html_a8efa7671c4b24700c2f22f63affdce9b"><div class="ttname"><a href="classpcl_1_1_moving_least_squares.html#a8efa7671c4b24700c2f22f63affdce9b">pcl::MovingLeastSquares::setUpsamplingRadius</a></div><div class="ttdeci">void setUpsamplingRadius(double radius)</div><div class="ttdoc">Set the radius of the circle in the local point plane that will be sampled</div><div class="ttdef"><b>Definition:</b> mls.h:222</div></div>
<div class="ttc" id="aclasspcl_1_1_moving_least_squares_html_ab0865f62d90c9fb0f45dd96e587fe84e"><div class="ttname"><a href="classpcl_1_1_moving_least_squares.html#ab0865f62d90c9fb0f45dd96e587fe84e">pcl::MovingLeastSquares::setSearchMethod</a></div><div class="ttdeci">void setSearchMethod(const KdTreePtr &amp;tree)</div><div class="ttdoc">Provide a pointer to the search object.</div><div class="ttdef"><b>Definition:</b> mls.h:132</div></div>
<div class="ttc" id="aclasspcl_1_1_moving_least_squares_html_ac29ad97b98353d64ce64e2ff924f7d20"><div class="ttname"><a href="classpcl_1_1_moving_least_squares.html#ac29ad97b98353d64ce64e2ff924f7d20">pcl::MovingLeastSquares::setUpsamplingMethod</a></div><div class="ttdeci">void setUpsamplingMethod(UpsamplingMethod method)</div><div class="ttdoc">Set the upsampling method to be used</div><div class="ttdef"><b>Definition:</b> mls.h:206</div></div>
<div class="ttc" id="aclasspcl_1_1_moving_least_squares_html_ac2c814527e15d4d3ff9a5ba5864b842d"><div class="ttname"><a href="classpcl_1_1_moving_least_squares.html#ac2c814527e15d4d3ff9a5ba5864b842d">pcl::MovingLeastSquares::setUpsamplingStepSize</a></div><div class="ttdeci">void setUpsamplingStepSize(double step_size)</div><div class="ttdoc">Set the step size for the local plane sampling</div><div class="ttdef"><b>Definition:</b> mls.h:235</div></div>
<div class="ttc" id="aclasspcl_1_1_moving_least_squares_html_ad168be16626ea58d1c31c321bd1d980f"><div class="ttname"><a href="classpcl_1_1_moving_least_squares.html#ad168be16626ea58d1c31c321bd1d980f">pcl::MovingLeastSquares::process</a></div><div class="ttdeci">void process(PointCloudOut &amp;output)</div><div class="ttdoc">Base method for surface reconstruction for all points given in &lt;setInputCloud (), setIndices ()&gt;</div><div class="ttdef"><b>Definition:</b> mls.hpp:57</div></div>
<div class="ttc" id="aclasspcl_1_1_moving_least_squares_html_ae5e4d16c7aae631ef02bf1ee843bd55e"><div class="ttname"><a href="classpcl_1_1_moving_least_squares.html#ae5e4d16c7aae631ef02bf1ee843bd55e">pcl::MovingLeastSquares::setSearchRadius</a></div><div class="ttdeci">void setSearchRadius(double radius)</div><div class="ttdoc">Set the sphere radius that is to be used for determining the k-nearest neighbors used for fitting.</div><div class="ttdef"><b>Definition:</b> mls.h:169</div></div>
<div class="ttc" id="aclasspcl_1_1_p_c_l_base_html_a1952d7101f3942bac3b69ed55c1ca7ea"><div class="ttname"><a href="classpcl_1_1_p_c_l_base.html#a1952d7101f3942bac3b69ed55c1ca7ea">pcl::PCLBase::setInputCloud</a></div><div class="ttdeci">virtual void setInputCloud(const PointCloudConstPtr &amp;cloud)</div><div class="ttdoc">Provide a pointer to the input dataset</div><div class="ttdef"><b>Definition:</b> pcl_base.hpp:66</div></div>
<div class="ttc" id="aclasspcl_1_1_point_cloud_html"><div class="ttname"><a href="classpcl_1_1_point_cloud.html">pcl::PointCloud&lt; pcl::PointXYZ &gt;</a></div></div>
<div class="ttc" id="aclasspcl_1_1_point_cloud_html_af16a62638198313b9c093127c492c884"><div class="ttname"><a href="classpcl_1_1_point_cloud.html#af16a62638198313b9c093127c492c884">pcl::PointCloud::points</a></div><div class="ttdeci">std::vector&lt; PointT, Eigen::aligned_allocator&lt; PointT &gt; &gt; points</div><div class="ttdoc">The point data.</div><div class="ttdef"><b>Definition:</b> point_cloud.h:410</div></div>
<div class="ttc" id="aclasspcl_1_1_s_h_o_t_estimation_o_m_p_html"><div class="ttname"><a href="classpcl_1_1_s_h_o_t_estimation_o_m_p.html">pcl::SHOTEstimationOMP</a></div><div class="ttdoc">SHOTEstimationOMP estimates the Signature of Histograms of OrienTations (SHOT) descriptor for a given...</div><div class="ttdef"><b>Definition:</b> shot_omp.h:71</div></div>
<div class="ttc" id="aclasspcl_1_1_scope_time_html"><div class="ttname"><a href="classpcl_1_1_scope_time.html">pcl::ScopeTime</a></div><div class="ttdoc">Class to measure the time spent in a scope</div><div class="ttdef"><b>Definition:</b> time.h:118</div></div>
<div class="ttc" id="aclasspcl_1_1rec__3d__framework_1_1_local_estimator_html"><div class="ttname"><a href="classpcl_1_1rec__3d__framework_1_1_local_estimator.html">pcl::rec_3d_framework::LocalEstimator</a></div><div class="ttdef"><b>Definition:</b> local_estimator.h:376</div></div>
<div class="ttc" id="aclasspcl_1_1rec__3d__framework_1_1_s_h_o_t_local_estimation_o_m_p_html"><div class="ttname"><a href="classpcl_1_1rec__3d__framework_1_1_s_h_o_t_local_estimation_o_m_p.html">pcl::rec_3d_framework::SHOTLocalEstimationOMP</a></div><div class="ttdef"><b>Definition:</b> shot_local_estimator_omp.h:22</div></div>
<div class="ttc" id="aclasspcl_1_1search_1_1_kd_tree_html"><div class="ttname"><a href="classpcl_1_1search_1_1_kd_tree.html">pcl::search::KdTree</a></div><div class="ttdoc">search::KdTree is a wrapper class which inherits the pcl::KdTree class for performing search function...</div><div class="ttdef"><b>Definition:</b> kdtree.h:63</div></div>
<div class="ttc" id="aclasspcl_1_1search_1_1_kd_tree_html_a457ebf1fc8f25e3b45d0bf9d55880f6f"><div class="ttname"><a href="classpcl_1_1search_1_1_kd_tree.html#a457ebf1fc8f25e3b45d0bf9d55880f6f">pcl::search::KdTree::setInputCloud</a></div><div class="ttdeci">void setInputCloud(const PointCloudConstPtr &amp;cloud, const IndicesConstPtr &amp;indices=IndicesConstPtr())</div><div class="ttdoc">Provide a pointer to the input dataset.</div><div class="ttdef"><b>Definition:</b> kdtree.hpp:77</div></div>
<div class="ttc" id="agroup__common_html_gaf5729fae15603888b49743b118025290"><div class="ttname"><a href="group__common.html#gaf5729fae15603888b49743b118025290">pcl::compute3DCentroid</a></div><div class="ttdeci">unsigned int compute3DCentroid(ConstCloudIterator&lt; PointT &gt; &amp;cloud_iterator, Eigen::Matrix&lt; Scalar, 4, 1 &gt; &amp;centroid)</div><div class="ttdoc">Compute the 3D (X-Y-Z) centroid of a set of points and return it as a 3D vector.</div><div class="ttdef"><b>Definition:</b> centroid.hpp:50</div></div>
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